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. 2026 Jan 4:e19110.
doi: 10.1002/advs.202519110. Online ahead of print.

Interlayer Dzyaloshinskii-Moriya Interaction in Synthetic Ferrimagnets for Spiking Neural Networks

Affiliations

Interlayer Dzyaloshinskii-Moriya Interaction in Synthetic Ferrimagnets for Spiking Neural Networks

Shen Li et al. Adv Sci (Weinh). .

Abstract

Interlayer Dzyaloshinskii-Moriya interaction (IL-DMI) in synthetic magnetic structures has attracted extensive interest for greatly facilitating deterministic spin-orbit torque (SOT)-driven information writing and topologically non-trivial 3D magnetic Hopfion forming. However, its distinct role in synthetic ferrimagnets (SFi) remains unexplored, where the conjunction of asymmetric magnetic moments and antisymmetric nature of IL-DMI leads to more diverse spin configurations and applications. Here, we reveal the unidirectional and chiral nature of IL-DMI in SFi, further unlocking application directions of IL-DMI in neuromorphic computing. Particularly, the IL-DMI-induced effective field increases approximately twentyfold while interacting with two asymmetric antiparallel-aligned moments, greatly facilitating future IL-DMI detection. Unlike previous digital-like switching, we find that the interplay of IL-DMI, SOT, and thermal effect gives rise to an analog-like switching behavior. Leveraging this, we develop an SOT-based non-probabilistic leaky-integrate-fire neuron device utilizing the micromagnetic analog-like switching model. Compared to probabilistic neurons, this provides a hardware support Spiking neural network, interlayer Dzyaloshinskii-Moriya interaction, spin-orbit torque, synthetic ferrimagnetsfor ultralow power, high-sparsity, and high-accuracy spiking neural networks.

Keywords: interlayer Dzyaloshinskii–Moriya interaction; spiking neural network; spin‐orbit torque; synthetic ferrimagnets.

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References

    1. K. Wang, V. Bheemarasetty, and G. Xiao, “Spin Textures in Synthetic Antiferromagnets: Challenges, Opportunities, and Future Directions,” APL Materials 11 (2023): 070902, https://doi.org/10.1063/5.0153349.
    1. R. A. Duine, K.‐J. Lee, S. S. P. Parkin, and M. D. Stiles, “Synthetic Antiferromagnetic Spintronics,” Nature Physics 14 (2018): 217–219, https://doi.org/10.1038/s41567‐018‐0050‐y.
    1. Y.‐C. Lau, D. Betto, K. Rode, J. M. D. Coey, and P. Stamenov, “Spin–orbit torque switching Without an External Field Using Interlayer Exchange Coupling,” Nature Nanotechnology 11 (2016): 758–762, https://doi.org/10.1038/nnano.2016.84.
    1. S.‐H. Yang, K.‐S. Ryu, and S. S. P. Parkin, “Domain‐Wall Velocities of up to 750 m s−1 driven by Exchange‐Coupling Torque in Synthetic Antiferromagnets,” Nature Nanotechnology 10 (2015): 221–226, https://doi.org/10.1038/nnano.2014.324.
    1. D. Houssameddine, J. F. Sierra, D. Gusakova, et al., “Spin Torque Driven Excitations in a Synthetic Antiferromagnet,” Applied Physics Letters 96 (2010): 072511, https://doi.org/10.1063/1.3314282.